Long non-coding RNAs(lncRNAs)regulate gene expression at the transcriptional,post-transcription-al,or epigenetic levels,and play crucial roles in tumor cell proliferation,invasion,apoptosis,and metabolism.With ongoing research,an increasing number of human microproteins encoded by lncRNAs have been discovered,although their complete functional characterization remains to be explored.This article reviews the research progress on the func-tions and partial mechanisms of the small integral membrane protein(SMIM)family encoded by lncRNAs in tumor ini-tiation and progression.

In recent years,artificial intelligence(AI)technologies,particularly those represented by deep learn-ing,have demonstrated tremendous potential in the advancement of medical applications.This article reviews recent re-search progress in AI applications for the diagnosis and treatment of triple-negative breast cancer,aiming to inform the development of clinically relevant AI algorithms that align with real-world practice scenarios.The ultimate objectives in-clude enhancing diagnostic accuracy through efficient computational approaches,reducing manual labor burdens,im-proving patient prognosis,and facilitating the identification of therapeutic targets in oncology through AI-driven predic-tive modeling.

Long non-coding RNAs(lncRNAs)regulate gene expression at the transcriptional,post-transcription-al,or epigenetic levels,and play crucial roles in tumor cell proliferation,invasion,apoptosis,and metabolism.With ongoing research,an increasing number of human microproteins encoded by lncRNAs have been discovered,although their complete functional characterization remains to be explored.This article reviews the research progress on the func-tions and partial mechanisms of the small integral membrane protein(SMIM)family encoded by lncRNAs in tumor ini-tiation and progression.

In recent years,artificial intelligence(AI)technologies,particularly those represented by deep learn-ing,have demonstrated tremendous potential in the advancement of medical applications.This article reviews recent re-search progress in AI applications for the diagnosis and treatment of triple-negative breast cancer,aiming to inform the development of clinically relevant AI algorithms that align with real-world practice scenarios.The ultimate objectives in-clude enhancing diagnostic accuracy through efficient computational approaches,reducing manual labor burdens,im-proving patient prognosis,and facilitating the identification of therapeutic targets in oncology through AI-driven predic-tive modeling.

This study was aimed to examine the effect of TREK-1 silencing on the function of astrocytes. Three 21-nucleotide small interfering RNA (siRNA) duplexes (siT1, siT2, siT3) targeting TREK-1 were constructed. Cy3-labeled dsRNA oligmers were used to determine the transfection efficiency in cultured astrocytes. TREK-1-specific siRNA duplexes (siT1, siT2, siT3) at the optimal concentration were transfected into cultured astrocytes, and the most efficient siRNA was identified by the method of immunocytochemical staining and Western blotting. The proliferation of astrocytes tranfected with TREK-1-targeting siRNA under hypoxia condition was measured by fluorescence-activated cell sorting (FACS). The results showed that TREK-1 was expressed in cultured astrocytes. The dsRNA oligmers targeting TREK-1 could be transfected efficiently in cultured astrocytes and down-regulate the expression of TREK-1 in astrocytes. Moreover, the down-regulation of TREK-1 in astrocytes contributed to the proliferation of astrocytes under hypoxia condition as determined by cell cycle analysis. It was concluded that siRNA is a powerful technique that can be used to knockdown the expression of TREK-1 in astrocytes, which helps further investigate the function of TREK-1 channel in astrocytes under physicological and pathological condition.
Animals ; Astrocytes ; physiology ; Cells, Cultured ; Gene Silencing ; physiology ; Potassium Channels ; Potassium Channels, Tandem Pore Domain ; genetics ; RNA Interference ; physiology ; RNA, Small Interfering ; genetics ; Rats

This study was aimed to examine the effect of TREK-1 silencing on the function of astrocytes. Three 21-nucleotide small interfering RNA (siRNA) duplexes (siT1, siT2, siT3) targeting TREK-1 were constructed. Cy3-labeled dsRNA oligmers were used to determine the transfection efficiency in cultured astrocytes. TREK-1-specific siRNA duplexes (siT1, siT2, siT3) at the optimal concentration were transfected into cultured astrocytes, and the most efficient siRNA was identified by the method of immunocytochemical staining and Western blotting. The proliferation of astrocytes tranfected with TREK-1-targeting siRNA under hypoxia condition was measured by fluorescence-activated cell sorting (FACS). The results showed that TREK-1 was expressed in cultured astrocytes. The dsRNA oligmers targeting TREK-1 could be transfected efficiently in cultured astrocytes and down-regulate the expression of TREK-1 in astrocytes. Moreover, the down-regulation of TREK-1 in astrocytes contributed to the proliferation of astrocytes under hypoxia condition as determined by cell cycle analysis. It was concluded that siRNA is a powerful technique that can be used to knockdown the expression of TREK-1 in astrocytes, which helps further investigate the function of TREK-1 channel in astrocytes under physicological and pathological condition.